model-code

examples/ace_step/model_inference/acestep-v15-turbo-shift3.py

@@ -0,0 +1,52 @@
+"""
+Ace-Step 1.5 Turbo (shift=3) — Text-to-Music inference example.
+
+Uses shift=3.0 (default turbo shift) for faster denoising convergence.
+"""
+from diffsynth.pipelines.ace_step import AceStepPipeline, ModelConfig
+import torch
+import soundfile as sf
+
+
+pipe = AceStepPipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[
+        ModelConfig(
+            model_id="ACE-Step/Ace-Step1.5",
+            origin_file_pattern="acestep-v15-turbo/model.safetensors"
+        ),
+        ModelConfig(
+            model_id="ACE-Step/Ace-Step1.5",
+            origin_file_pattern="acestep-v15-turbo/model.safetensors"
+        ),
+        ModelConfig(
+            model_id="ACE-Step/Ace-Step1.5",
+            origin_file_pattern="Qwen3-Embedding-0.6B/model.safetensors"
+        ),
+    ],
+    tokenizer_config=ModelConfig(
+        model_id="ACE-Step/Ace-Step1.5",
+        origin_file_pattern="Qwen3-Embedding-0.6B/"
+    ),
+    vae_config=ModelConfig(
+        model_id="ACE-Step/Ace-Step1.5",
+        origin_file_pattern="vae/"
+    ),
+)
+
+prompt = "An explosive, high-energy pop-rock track with anime theme song feel"
+lyrics = "[Intro]\n\n[Verse 1]\nRunning through the neon lights\nChasing dreams across the night\n\n[Chorus]\nFeel the fire in my soul\nMusic takes complete control"
+
+audio = pipe(
+    prompt=prompt,
+    lyrics=lyrics,
+    duration=30.0,
+    seed=42,
+    num_inference_steps=8,
+    cfg_scale=1.0,
+    shift=3.0,
+)
+
+sf.write("acestep-v15-turbo-shift3.wav", audio.cpu().numpy(), pipe.sample_rate)
+print(f"Saved, shape: {audio.shape}")